Quantum dot–based time-bin QKD achieves stable, long-distance secure communication with practical performance.
Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Abstract: Change detection plays a vital role in numerous real-world domains, aiming to accurately identify regions that have changed between two temporally distinct images. Capturing the complex ...
The implementation is intentionally explicit and educational, avoiding high-level abstractions where possible. . ├── config.py # Central configuration file defining model hyperparameters, training ...
Most learning-based speech enhancement pipelines depend on paired clean–noisy recordings, which are expensive or impossible to collect at scale in real-world conditions. Unsupervised routes like ...
NVIDIA introduces Riva TTS models enhancing multilingual speech synthesis and voice cloning, with applications in AI agents, digital humans, and more, featuring advanced architecture and preference ...
Abstract: Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for ...
I want to train pretrain a sentence transformer using TSDAE. We have previously used all-MiniLM-L6-v2 as a checkpoint where we finetuned with MultipleNegativeRankingLoss with the main downstream task ...
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